Do Tourists like Nature?

Do tourists care about national parks? I think the answer is obviously yes, as the global success of the American National Park system suggests. The draw for travelers is obvious for the United States, with its incredible and uniquely well-preserved natural landscape. The challenge is if a country with fewer natural treasures than the US can also expect tourists to travel to their national parks.

This article is a quick excursion looking at some data I compiled on national parks in Germany. The question I want to ask is if the presence of a national park is associated with increased tourist traffic. That is, for my tourist ranking scheme, should I include a measure of natural beauty in the ranking?

The topic has appeared in the literature in several places and is inconsistent, to say the least. The role of natural beauty in tourism ranges from the absurdly high “60% of all international tourists are chasing nature’s bounty” to the “ecotourism statistics are driven by misguided academic agendas” (McKercher 2014). The analysis here does not aim to replicate any of the more rigorous studies but rather see if I can use my data regarding national parks to gauge levels of over-tourism.

Using QGIS, I collected two statistics, one looking at the percentage of each administrative county set aside as a national park or federal nature preserve. The second is simply a boolean variable that indicates if the county has at least some national parkland within its borders.

The code for all of the graphs can be seen in my GitHub repository. I tried to optimize them as much as possible for mobile view, but some will be better seen in desktop mode.

We can see in the data that there is a weak association between national parkland and tourist overnight stays. The presence of many counties without national parks heavily skews the data. This non-linear abnormality is challenging to negotiate with, so I also created a binary variable that merely indicates the presence of a national park.

The variable is also largely uncorrelated with the other variables. As you would expect, national parks are negatively associated with infrastructure variables such as railroads and GDP. It does have a mild positive association with the number of hotels and overnight stays, suggesting there may be a link here. To see an overview of the other variables, see here.

Overnights p.C. and Parkland
Y Var:ln(Overnights)R-Squared:0.783
Model:OLSAdj. R-Squared:0.777
No. Obs:385Covar. Type:HC3
X VarCoefStd ErrtP>|t|
Constant-2.16180.886-2.4390.015
Momentum 1Yr0.73490.4651.5810.115
Momentum 5Yr*0.39130.1672.3470.019
Log Railroad p.Km20.01540.0570.2710.787
Park Area (%)0.00050.0010.7150.475
Log GDP p.C.*0.18530.0722.5690.011
Log Hotels p.C.***1.10120.03432.4750.000
Monuments***0.01880.0044.6830.000
Urban Area (%)***0.00970.0024.6670.000
Coast***0.68250.1116.1640.000
Vineyard Area (%)*-0.01220.005-2.5060.013
Overnights p.C. and Parkland
Y Var:ln(Overnights)R-Squared:0.783
Model:OLSAdj. R-Squared:0.777
No. Obs:385Covar. Type:HC3
X VarCoefStd ErrtP>|t|
Constant-2.16290.883-2.4500.015
Momentum 1Yr0.75820.4611.6450.101
Momentum 5Yr*0.38400.1642.3390.020
Log Railroad p.Km20.01790.0570.3160.752
Park Area (%)0.03640.0450.8010.424
Log GDP p.C.*0.18630.0722.6030.010
Log Hotels p.C.***1.10570.03234.1750.000
Monuments***0.01840.0044.5410.000
Urban Area (%)***0.00980.0024.6810.000
Coast***0.66790.1086.1700.000
Vineyard Area (%)*-0.01220.005-2.5130.012

In the first two models here, we see that both variables proxying the tourist draw of national parks are very insignificant. The reason is that the main nature-based attraction for tourists is the beach. Tourism relies heavily on conspicuous consumption to fund trips, and trees are bad at this sort of thing. Experiencing nature requires effort. Most tourists will find the reward for this effort easily substitutable with a low-effort selfie in front of the Eifel Tower. I consider eco- or nature tourists a member of the “special interest” travelers club.

Foreign Overnights p.C. and Parkland
Y Var:ln(Overnights)R-Squared:0.600
Model:OLSAdj. R-Squared:0.589
No. Obs:385Covar. Type:HC3
X VarCoefStd ErrtP>|t|
Constant-12.85161.732-7.4200.000
Momentum 1Yr-0.32810.716-0.4580.647
Momentum 5Yr***1.11910.2794.0040.000
Log Railroad p.Km20.00580.1020.0570.955
Park Area (%)0.00020.0010.1520.879
Log GDP p.C.***0.98950.1327.4830.000
Log Hotels p.C.***0.97300.06714.4650.000
Monuments***0.02300.0054.6600.000
Urban Area (%)***0.01540.0034.7110.000
Coast-0.14010.201-0.6970.486
Vineyard Area (%)0.00450.0110.4170.677
Domestic Overnights p.C. and Parkland
Y Var:ln(Overnights)R-Squared:0.540
Model:OLSAdj. R-Squared:0.528
No. Obs:385Covar. Type:HC3
X VarCoefStd ErrtP>|t|
Constant10.17851.6786.0670.000
Momentum 1Yr0.11490.9560.1200.904
Momentum 5Yr0.29210.3010.9690.333
Log Railroad p.Km20.03740.0990.3760.707
Park Area (%)0.00060.0010.5500.583
Log GDP p.C.0.15960.1461.0950.274
Log Hotels p.C.***0.81440.06512.4410.000
Monuments***0.08300.0155.6260.000
Urban Area (%)*0.00740.0041.8570.064
Coast***0.80030.1974.0710.000
Vineyard Area (%)-0.00690.009-0.7730.440

I can, however, use the data available and break down overnight stays into categories of guests by foreign and domestic. We might expect that foreign tourists are less interested in national parks, as most countries have national parks, and there is less reason to travel abroad to see a potentially homogenous destination. We see that national parks remain irrelevant to both parties but that beaches are significant only in predicting overnight stays by domestic tourists. More evidence suggests that the average national park is less likely to attract tourists than a sandy beach.

In the future, I will probably not include national park statistics in my final ranking, but I will see if I can create a more detailed special-interest travel index that does.

Articles in this Series

Ranking the Regions

Ranking the Regions

The website uses a simple ranking methodology to help categorize travel destinations into various categories. People travel for different reasons and have different expectations. Some travelers do so with a…

Counting the Hidden Gems

Counting the Hidden Gems

The final step in this model-building process is ranking the German counties and the aggregation into my geographic schema. The goal is to build a metric that might help me…

If You Build It – Will They Come?

If You Build It – Will They Come?

“If you build it – they will come” is a quote often used satirically to deride investors in white elephant projects. However, logically, the most critical determinant in measuring tourist…

Counting Tourists

Counting Tourists

The holy grail of quantitative tourism would be a near-objective measure of “too many” tourists. Such information would allow airlines, tour providers, and municipalities to direct and redirect tourists to…

Is Anything Authentic Anymore?

Is Anything Authentic Anymore?

Have you ever been to a tourist trap or a location with so many people that the entire trip felt pointless or disappointing? Maybe you walked into a local shop…

Sources

McKercher B., Prideaux B. 2014. “Academic Myths of Tourism.” Annals of Tourism Research 46:16-28.

Leave a Reply